@inproceedings{li-etal-2024-refiner,
title = "$\textit{Refiner}$: Restructure Retrieved Content Efficiently to Advance Question-Answering Capabilities",
author = "Li, Zhonghao and
Hu, Xuming and
Liu, Aiwei and
Zheng, Kening and
Huang, Sirui and
Xiong, Hui",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-emnlp.500",
pages = "8548--8572",
}
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%0 Conference Proceedings
%T Refiner: Restructure Retrieved Content Efficiently to Advance Question-Answering Capabilities
%A Li, Zhonghao
%A Hu, Xuming
%A Liu, Aiwei
%A Zheng, Kening
%A Huang, Sirui
%A Xiong, Hui
%Y Al-Onaizan, Yaser
%Y Bansal, Mohit
%Y Chen, Yun-Nung
%S Findings of the Association for Computational Linguistics: EMNLP 2024
%D 2024
%8 November
%I Association for Computational Linguistics
%C Miami, Florida, USA
%F li-etal-2024-refiner
%U https://aclanthology.org/2024.findings-emnlp.500
%P 8548-8572
Markdown (Informal)
[Refiner: Restructure Retrieved Content Efficiently to Advance Question-Answering Capabilities](https://aclanthology.org/2024.findings-emnlp.500) (Li et al., Findings 2024)
ACL